st: RE: summarize correlation matrix

[Nick Cox <n.j.cox@durham.ac.uk>]

-corrci- (SJ) makes this easy. -corrci- was written primarily to support confidence interval calculation for correlations but has an option to save a correlation matrix to a dataset. The analyses allowed by -corrci- raise the question of whether you should be summarizing correlations on a z scale, not an r scale. 

See 

SJ-10-4 pr0041_1  . . . . . . . . . . . . . . . . . Software update for corrci
        (help corrci, corrcii if installed) . . . . . . . . . . . .  N. J. Cox
        Q4/10   SJ 10(4):691
        update to fix corrci so that it always saves r-class results

SJ-8-3  pr0041  .  Speaking Stata: Corr. with confidence, Fisher's z revisited
        (help corrci, corrcii if installed) . . . . . . . . . . . .  N. J. Cox
        Q3/08   SJ 8(3):413--439
        reviews Fisher's z transformation and its inverse, the
        hyperbolic tangent, and reviews their use in inference
        with correlations

The suggestion is that you read the paper in SJ 8-3 ( which is accessible at http://www.stata-journal.com/sjpdf.html?articlenum=pr0041 ) 

but download the updated software from the files for SJ 10-4. 

All that said, I am not sure quite what useful information is given by some of these numbers. I think of problems in which showing the overall distribution of the correlations is of some descriptive value, which was precisely why I provided that option, but the standard deviation? Also, if correlations are generally weak, then either you are summarizing noise or you are asking the wrong questions about relationships! 

Nick 
n.j.cox@durham.ac.uk 


-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Cohen, Elan
Sent: 18 May 2012 16:21
To: statalist@hsphsun2.harvard.edu
Subject: st: summarize correlation matrix

I have a large correlation matrix after running -corr- on my dataset.  I'd now like to summarize that matrix, i.e. get the mean, sd, plot a histogram of the p*(p-1)/2 correlation values (where p is the number of variables).  I'm not quite savvy enough in Mata and it's proving difficult in standard Stata programming.  I'd greatly appreciate an answer using either.

Thank you,

- Elan


--
Elan D Cohen, MS
Center for Research on Health Care Data Center
University of Pittsburgh 
cohened@upmc.edu 



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